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Oct 04, 2019 EVENTS
Excitement Builds for Dr Belinda Nedjai's Seminar on Non-invasive methylation biomarkers for early detection of HPV-related cancers.

Forte are please to announce that Dr Belinda Nedjai will give a talk on Non-invasive methylation biomarkers for early detection of HPV-related cancers.

Dr Nedjai is Senior Research Fellow and Head of the Molecular Epidemiology laboratory at Bart’s Cancer institute at Queen Mary university London. She is also the scientific coordinator of aspirin for cancer prevention collaboration (AsCaP). She holds a PhD in functional genomics in inflammatory disorders. She has expertise in biomarkers identification and validation using deep sequencing and high throughput techniques (WES, RNA seq, miRNA and methylome). Her team aim is to identify and develop cost-effective tests for the early detection and the prediction of outcomes in cancer patients. Recent successes include the identification of methylation biomarkers to manage patients infected by papillomavirus developing HPV related cancers and an alternative epigenetic approach for management of men with prostate cancer.

Abstract

HPV infection has a critical role in common dermatologic and sexually transmitted diseases, as well as in some of the most frequent cancers worldwide. The HPV-associated disease burden is higher than that reported for any other infectious agent worldwide, with a larger burden observed in women than in men. The rapidly rising male share of the total burden underlines the prioritization of male HPV-related disease in prevention programmes, especially oropharyngeal cancer.

We have developed a triage classifier (S5) for the detection of HPV-related precancer lesions (anal, cervical, oropharyngeal), based on DNA methylation of HPV16, HPV18, HPV31 and HPV33 combined with the human gene EPB41L3 (Brentnall et al., 2015). S5 classifier can predict the progression from normal to cervical cancer up to 5 years in advance.

We also tested this classifier on two non-invasive cervical cancer specimens: a self-collected vaginal sample and urine. We demonstrated that S5 identify women who are CIN2+ using self-collected samples.

Come to the talk on Monday 14th of October at 12.00 the University of Southampton, Building 53 room 4025.